Video security systems have been traditionally used to help protect people, property, and reduce crime for homeowners and businesses alike and have become an increasingly cost-effective tool to reduce risk. Modern systems with video analytics capabilities provide the ability to detect and track individuals and objects within monitored scenes. These systems can provide both live monitoring of individuals, and forensic analysis of saved security video data to spot trends and search for specific behaviors of interest.
More recently, these video systems have been used to track usage and facilitate resource management, in general. For example, of increasing interest is the ability to identify and analyze a notional queue of objects. Examples here might be a line of individuals queueing at a point of sale location or a line of cars at a drive up window.
A number of solutions exist for analyzing queues. In one, areas of interest are defined within a frame of video to provide an estimate of the number of individuals in the area. Another solution defines an area within a scene of video to detect a queue of vehicles in the scene, where the region definition is calibrated in conjunction with radar-based sensors mounted in traffic lanes. Yet another solution defines separate regions within the scene and estimates wait times for objects in the queue relative to a difference in service times of two or more events associated with objects within the regions. In yet another example of analyzing queues, a system divides scene into slots, where each slot is approximately the size of an individual. The system detects a queue within the video based on motion of the individuals across the slots and counts the individuals that occupy the slots. Finally, still another system estimates wait times for individuals performing retail transactions in a notional transaction queue. The system first identifies each individual and the items they present for transaction at a point of sale location. Then, the system determines the time it takes to transact each item, and estimates the total service time for an individual as the aggregate of the transaction processing times for their items.